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Optimisation process determines risk versus reward

6th May 2016

By: Kimberley Smuts

Creamer Media Reporter

  

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The use of multiparametric block models, which contain more than just geological data, to analyse the risks associated with the mining process, allow more informed business decisions to be made on the basis of risk and exposure to that risk.

This is according to The MSA Group mine optimisation and planning principal consultant Richard Gawthorpe, who notes that, when working an openpit resource, the group goes through an optimisation process to determine the net present value (NPV) generated from a particular geological resource.

Financial and technical parameters are used to evaluate each block in a block model, representing the resource.

Each block contains a particular quantity of saleable material, which can be used to calculate how much revenue will be generated and how much cost will be incurred. Using the slope parameters, the shell or the shape of the ultimate pit which generates the maximum NPV is defined, explains Gawthorpe.

“Traditionally, we have always used optimisation engines to generate a shell that enhances the monetary value and then develop a mining sequence and a schedule that spreads the mining material over a timeline, which will forecast the achievable NPV.”

However, he explains that there are additional methodologies in the field of optimisation that do more than just increase the NPV. There is also a series of analyses that can be carried out using the optimisation process to quantify several risk types, either to try and reduce that risk or at least understand it better. The results of this analysis can then be built into a mitigation process that can limit exposure to risk, such as slope failure or depressed commodity prices.

Gawthorpe further explains that, by using conditional simulation to estimate a series of grades for each block in the resource model, the geological risk can be quantified. The optimisation process can be run multiple times on each individual simu- lated grade, generating a series of ultimate pit shells.

By representing the number of times that each block is included in the shells as a percentage of the number of simulations, the risk of the block not meeting the economic criteria can be illustrated and used as a cutoff. In addition, the coefficient of variance (the standard deviation of the grades divided by the mean) can be used in the sequencing and scheduling process to blend high- and low-risk areas, or forecast the risk profile over time, and allow time for actions to reduce the risk.

He explains that geotechnical risk can also be quantified by running the optimisation process at a series of increasing slope angles. Increasing the slope angle will increase the NPV, by reducing waste stripping, but will also increase the probability of slope failure. The probability of failure can be lowered to acceptable levels by mitigating actions, such as grouting or installing cable bolts. By combining the cost of this with the NPV, a hill of value is created indicating the optimal slope and the support criteria necessary.

Also requiring consideration are the mining risks associated with growing the value of the resources in the ground and whether the mine’s cutoff grade needs to be increased to boost the metal throughput.

The cost of the additional equipment needed to increase the flow of material being mined should also be examined. The cost of equipment needs to be weighed against the benefit of the value generated as a result of expanding an opencast mine’s metal throughput. “This should determine the optimal mining rate from an economic point of view,” states Gawthorpe.

Environmental risks also present a series of surface restrictions that prevent the mining of certain areas. These restrictions include minerals being located outside the mining property, an area being inhabited by a township, an endangered species living in the area or the property crossing into a national park.

Gawthorpe notes that these restrictions are looked at as boundaries, which hold certain value thresholds. The optimisation process looks at the various scenarios through which these boundaries can be removed or circumvented to determine whether the value of the minerals located in that area outweighs the cost of removing the boundary.

Another feature of the optimisation process is its ability to review the scheduling process when a boundary needs to be removed. Such an approach can contain costs at an early stage and ensures that the necessary material is available when needed, Gawthorpe points out.

“These risk analysis processes further improve resource use. This is not the only way to go about [improving the efficiency of] projects, but you have to decide whether you want to chance exposure to risk or play it safe,” he concludes.

Edited by Tracy Hancock
Creamer Media Contributing Editor

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